1. Field of the Invention
This invention relates generally to a spectral band analysis system and, more particularly, to a spectral band analysis system for determining appropriate frequency bands and associated integration times that will increase the signal-to-noise ratio between the spectral signature of an object or objects of interest and the spectral signature of background noise and clutter so as to effectively identify the objects within the background.
2. Discussion of the Related Art
Strategic and tactical detection and tracking systems which detect and track objects or targets of interest that are moving relative to the earth's surface are known in the art. These detection and tracking systems include ground based and air based systems that detect and track strategic objects such as aircraft, missiles, motor vehicles and the like. Although many different types of detection and tracking systems are known, the basic goal of each system is to provide a very high probability of detecting the target of interest when the target is present, while at the same time preventing the system from indicating a target detection when no target is present. In other words, these systems must have a high signal-to-noise ratio (SNR) between the target signals and background or noise signals in order to effectively separate the target from any background clutter or noise.
One system of the type discussed above that performs missile launch detection and tracking from a satellite orbiting the earth is disclosed in U.S. Pat. No. 5,300,780, issued Apr. 5, 1994, titled MISSILE SURVEILLANCE METHOD AND APPARATUS, assigned to the assignee of the instant application, and herein incorporated by reference. This detection and tracking system incorporates an infrared sensor which detects infrared radiation being emitted from the Earth's surface. The sensor includes a series of detectors where each detector absorbs energy from a particular area or scene of the Earth's surface. The detectors will absorb energy of differing intensities for each wavelength within the frequency range of the sensor from the emissions of the objects in the scene. The different background clutter objects, such as clouds, and the objects of interest will emit infrared energy intensities at the different wavelengths within the frequency range being sensed. When viewed as an image of a particular area of the earth's surface, each detector intensity and location is referred to as a pixel (picture element).
The radiation received by the sensor is sent through a series of color filters before the radiation impinges the detectors. The color filters separate the frequency range into a series of frequency bands where each band is a continuum of wavelengths. The filters are incorporated on a wheel such that as the wheel turns, each filter will receive the impinging radiation. The rotational speed and operation of the wheel is selected such that each filter receives the radiation for a predetermined time in order to set an integration time for each band. As will be discussed below, the filters and integration times are selected to increase the SNR between the background and the targets of interest.
FIG. 1 shows a graphical representation of the signature spectral pattern of background emissions and the emissions of a particular target of interest across the frequency range of the sensor. The relative energy for each wavelength is given in the vertical axis and the frequency range is given in wavelength increments on the horizontal axis. The relative energy is not the actual energy but is a relational value with respect to all of the energies. The infrared wavelength range is between 2.0 and 5.0 .mu.m and each slash along the wavelength axis is about 50 nm.
In order to more reliably detect and track a target of interest, it is necessary to know how to selectively determine which bands and associated integration times within the frequency range being sensed best separate the target when compared with the background/clutter emissions at those bands. Two factors enable the target emissions to be more effectively separated from background clutter emissions. First, the difference in intensities between the target signal and the background/clutter signal. Second, the shape of the waveform of the target signal when compared to the shape of the background/clutter waveform. By combining these factors, the SNR between the target emissions signal and the background/clutter noise signal can be increased in order to more reliably detect and track the target.
The particular wavelength bands and integration times which are used to distinguish the target signal from the background signal are selected in the prior art by visually inspecting the spectral signatures of the target and background. The top row of black bars labeled "initial bands" beneath the horizontal axis in FIG. 1 shows seven different bands which have been determined to be the more desirable areas where these two factors would best separate the target signal from the background noise signal. Depending on the particular number of targets being monitored, the number of bands will be chosen accordingly. Once the bands are selected, the color filters of the targeting system can then be set. In a multi spectral (MS) system, the number of bands is typically less than ten. In a hyper spectral (HS) system, the number of bands is typically greater than one hundred.
For the particular system discussed above with reference to U.S. Pat. No. 5,300,780, an algorithm (set out below) is used which includes a number of attributes for dealing with false target rejection and background uncertainty when compared with conventional matched filtering. A mix of expert experience, feedback from real systems, and simulations have established band selection and integration time with good results. However, the algorithm has some characteristics related to the need for target-to-background orthogonality which may not be obvious and as such the best band choices to optimize target-to-background or target-to-target separation and band integration time may not be used. Specifically with regard to MS system, the complications of overlapping bands and band-to-band correlation degrades this optimization process. Therefore, the prior art process of selecting bands and associated integration times does not provide the optimal results for such a system.
What is needed is a band analysis mechanism which determines the most appropriate wavelength bands and integration times which would best distinguish the target emissions from the background emissions in order to more reliably detect a target of interest. It is therefore an object of the present invention to provide such a band analysis mechanism.